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Article: Model selection in time series studies of influenza-associated mortality

TitleModel selection in time series studies of influenza-associated mortality
Authors
KeywordsAcute respiratory tract disease
Bayes theorem
Generalized cross validation
Health hazard
Intermethod comparison
Issue Date2012
PublisherPublic Library of Science. The Journal's web site is located at http://www.plosone.org/home.action
Citation
Plos One, 2012, v. 7 n. 6 How to Cite?
Abstract
Background: Poisson regression modeling has been widely used to estimate influenza-associated disease burden, as it has the advantage of adjusting for multiple seasonal confounders. However, few studies have discussed how to judge the adequacy of confounding adjustment. This study aims to compare the performance of commonly adopted model selection criteria in terms of providing a reliable and valid estimate for the health impact of influenza. Methods: We assessed four model selection criteria: quasi Akaike information criterion (QAIC), quasi Bayesian information criterion (QBIC), partial autocorrelation functions of residuals (PACF), and generalized cross-validation (GCV), by separately applying them to select the Poisson model best fitted to the mortality datasets that were simulated under the different assumptions of seasonal confounding. The performance of these criteria was evaluated by the bias and root-mean-square error (RMSE) of estimates from the pre-determined coefficients of influenza proxy variable. These four criteria were subsequently applied to an empirical hospitalization dataset to confirm the findings of simulation study. Results: GCV consistently provided smaller biases and RMSEs for the influenza coefficient estimates than QAIC, QBIC and PACF, under the different simulation scenarios. Sensitivity analysis of different pre-determined influenza coefficients, study periods and lag weeks showed that GCV consistently outperformed the other criteria. Similar results were found in applying these selection criteria to estimate influenza-associated hospitalization. Conclusions: GCV criterion is recommended for selection of Poisson models to estimate influenza-associated mortality and morbidity burden with proper adjustment for confounding. These findings shall help standardize the Poisson modeling approach for influenza disease burden studies. © 2012 Wang et al.
Descriptioneid_2-s2.0-84862699414
Persistent Identifierhttp://hdl.handle.net/10722/159710
ISSN
2013 Impact Factor: 3.534
2013 SCImago Journal Rankings: 1.724
ISI Accession Number ID
References

 

Author Affiliations
  1. The University of Hong Kong
  2. Queen Mary Hospital Hong Kong
DC FieldValueLanguage
dc.contributor.authorWang, XLen_HK
dc.contributor.authorYang, Len_HK
dc.contributor.authorChan, KPen_HK
dc.contributor.authorChiu, SSen_HK
dc.contributor.authorChan, KHen_HK
dc.contributor.authorPeiris, JSMen_HK
dc.contributor.authorWong, CMen_HK
dc.date.accessioned2012-08-16T05:54:48Z-
dc.date.available2012-08-16T05:54:48Z-
dc.date.issued2012en_HK
dc.identifier.citationPlos One, 2012, v. 7 n. 6en_HK
dc.identifier.issn1932-6203en_HK
dc.identifier.urihttp://hdl.handle.net/10722/159710-
dc.descriptioneid_2-s2.0-84862699414-
dc.description.abstractBackground: Poisson regression modeling has been widely used to estimate influenza-associated disease burden, as it has the advantage of adjusting for multiple seasonal confounders. However, few studies have discussed how to judge the adequacy of confounding adjustment. This study aims to compare the performance of commonly adopted model selection criteria in terms of providing a reliable and valid estimate for the health impact of influenza. Methods: We assessed four model selection criteria: quasi Akaike information criterion (QAIC), quasi Bayesian information criterion (QBIC), partial autocorrelation functions of residuals (PACF), and generalized cross-validation (GCV), by separately applying them to select the Poisson model best fitted to the mortality datasets that were simulated under the different assumptions of seasonal confounding. The performance of these criteria was evaluated by the bias and root-mean-square error (RMSE) of estimates from the pre-determined coefficients of influenza proxy variable. These four criteria were subsequently applied to an empirical hospitalization dataset to confirm the findings of simulation study. Results: GCV consistently provided smaller biases and RMSEs for the influenza coefficient estimates than QAIC, QBIC and PACF, under the different simulation scenarios. Sensitivity analysis of different pre-determined influenza coefficients, study periods and lag weeks showed that GCV consistently outperformed the other criteria. Similar results were found in applying these selection criteria to estimate influenza-associated hospitalization. Conclusions: GCV criterion is recommended for selection of Poisson models to estimate influenza-associated mortality and morbidity burden with proper adjustment for confounding. These findings shall help standardize the Poisson modeling approach for influenza disease burden studies. © 2012 Wang et al.en_HK
dc.languageengen_US
dc.publisherPublic Library of Science. The Journal's web site is located at http://www.plosone.org/home.actionen_HK
dc.relation.ispartofPLoS ONEen_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectAcute respiratory tract disease-
dc.subjectBayes theorem-
dc.subjectGeneralized cross validation-
dc.subjectHealth hazard-
dc.subjectIntermethod comparison-
dc.titleModel selection in time series studies of influenza-associated mortalityen_HK
dc.typeArticleen_HK
dc.identifier.emailChiu, SS: ssschiu@hku.hken_HK
dc.identifier.emailPeiris, JSM: malik@hkucc.hku.hken_HK
dc.identifier.authorityChiu, SS=rp00421en_HK
dc.identifier.authorityPeiris, JSM=rp00410en_HK
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1371/journal.pone.0039423en_HK
dc.identifier.pmid22745751-
dc.identifier.scopuseid_2-s2.0-84862699414en_HK
dc.identifier.hkuros202482en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-84862699414&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume7en_HK
dc.identifier.issue6en_HK
dc.identifier.spagee39423en_US
dc.identifier.epagee39423en_US
dc.identifier.isiWOS:000305693200075-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridWang, XL=55258938700en_HK
dc.identifier.scopusauthoridYang, L=7406279703en_HK
dc.identifier.scopusauthoridChan, KP=27171298000en_HK
dc.identifier.scopusauthoridChiu, SS=7202291500en_HK
dc.identifier.scopusauthoridChan, KH=7406034307en_HK
dc.identifier.scopusauthoridPeiris, JSM=7005486823en_HK
dc.identifier.scopusauthoridWong, CM=37089643600en_HK

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